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Article: CIDER: Corrected inverse-denoising filter for image restoration

TitleCIDER: Corrected inverse-denoising filter for image restoration
Authors
KeywordsInverse filter
Regularization
Restoration
Wavelet denoising
Issue Date2007
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
Lecture Notes In Computer Science (Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics), 2007, v. 4679 LNCS, p. 112-126 How to Cite?
AbstractIn this paper we propose and develop a new algorithm, Corrected Inverse-Denoising filtER (CIDER) to restore blurred and noisy images. The approach is motivated by a recent algorithm ForWaRD, which uses a regularized inverse filter followed by a wavelet denoising scheme. In ForWaRD, the restored image obtained by the regularized inverse filter is a biased estimate of the original image. In CIDER, the correction term is added to this restored image such that the resulting one is an unbiased estimator. Similarly, the wavelet denoising scheme can be applied to suppress the residual noise. Experimental results show that the performance of CIDER is better than other existing methods in our comparison study. © Springer-Verlag Berlin Heidelberg 2007.
Persistent Identifierhttp://hdl.handle.net/10722/119237
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252
References

 

DC FieldValueLanguage
dc.contributor.authorWen, YWen_HK
dc.contributor.authorNg, Men_HK
dc.contributor.authorChing, WKen_HK
dc.date.accessioned2010-09-26T08:42:18Z-
dc.date.available2010-09-26T08:42:18Z-
dc.date.issued2007en_HK
dc.identifier.citationLecture Notes In Computer Science (Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics), 2007, v. 4679 LNCS, p. 112-126en_HK
dc.identifier.issn0302-9743en_HK
dc.identifier.urihttp://hdl.handle.net/10722/119237-
dc.description.abstractIn this paper we propose and develop a new algorithm, Corrected Inverse-Denoising filtER (CIDER) to restore blurred and noisy images. The approach is motivated by a recent algorithm ForWaRD, which uses a regularized inverse filter followed by a wavelet denoising scheme. In ForWaRD, the restored image obtained by the regularized inverse filter is a biased estimate of the original image. In CIDER, the correction term is added to this restored image such that the resulting one is an unbiased estimator. Similarly, the wavelet denoising scheme can be applied to suppress the residual noise. Experimental results show that the performance of CIDER is better than other existing methods in our comparison study. © Springer-Verlag Berlin Heidelberg 2007.en_HK
dc.languageengen_HK
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_HK
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_HK
dc.subjectInverse filteren_HK
dc.subjectRegularizationen_HK
dc.subjectRestorationen_HK
dc.subjectWavelet denoisingen_HK
dc.titleCIDER: Corrected inverse-denoising filter for image restorationen_HK
dc.typeArticleen_HK
dc.identifier.emailChing, WK:wching@hku.hken_HK
dc.identifier.authorityChing, WK=rp00679en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-38149101697en_HK
dc.identifier.hkuros134001en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-38149101697&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume4679 LNCSen_HK
dc.identifier.spage112en_HK
dc.identifier.epage126en_HK
dc.publisher.placeGermanyen_HK
dc.identifier.scopusauthoridWen, YW=7401777008en_HK
dc.identifier.scopusauthoridNg, M=34571761900en_HK
dc.identifier.scopusauthoridChing, WK=13310265500en_HK

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